elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Edge-Convolution Point Net for Semantic Segmentation of Large-Scale Point Clouds

Contreras, Jhonatan and Denzler, Joachim (2019) Edge-Convolution Point Net for Semantic Segmentation of Large-Scale Point Clouds. In: IGARSS 2019 - IEEE International Geoscience and Remote Sensing Symposium, pp. 5236-5239. IEEE. IGARSS 2019 - IEEE International Geoscience and Remote Sensing Symposium, 28 July-2 Aug. 2019, Yokohama, Japan. DOI: 10.1109/IGARSS.2019.8899303 ISBN 978-1-5386-9154-0 ISSN 2153-7003

Full text not available from this repository.

Official URL: https://ieeexplore.ieee.org/abstract/document/8899303/authors#authors

Abstract

In this paper, we propose a deep learning-based framework which can manage large-scale point clouds of outdoor scenes with high spatial resolution. For large and high-resolution outdoor scenes, point-wise classification approaches are often an intractable problem. Analogous to Object-Based Image Analysis (OBIA), our approach segments the scene by grouping similar points together to generate meaningful objects. Later, our net classifies segments instead of individual points using an architecture inspired by PointNet, which applies Edge convolutions. This approach is trained using both visual and geometrical information. Experiments show the potential of this task even for small training sets. Furthermore, we can show competitive performance on a Large-scale Point Cloud Classification Benchmark

Item URL in elib:https://elib.dlr.de/133222/
Document Type:Conference or Workshop Item (Speech)
Title:Edge-Convolution Point Net for Semantic Segmentation of Large-Scale Point Clouds
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Contreras, JhonatanJhonatan.Contreras (at) dlr.dehttps://orcid.org/0000-0002-0491-9896
Denzler, JoachimFSU Jenahttps://orcid.org/0000-0002-3193-3300
Date:14 November 2019
Journal or Publication Title:IGARSS 2019 - IEEE International Geoscience and Remote Sensing Symposium
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.1109/IGARSS.2019.8899303
Page Range:pp. 5236-5239
Publisher:IEEE
Series Name:IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium
ISSN:2153-7003
ISBN:978-1-5386-9154-0
Status:Published
Keywords:Semantic segmentation, Point Clouds, Deep Learning, Outdoor Scenes.
Event Title:IGARSS 2019 - IEEE International Geoscience and Remote Sensing Symposium
Event Location:Yokohama, Japan
Event Type:international Conference
Event Dates:28 July-2 Aug. 2019
Organizer:IEEE
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:other
DLR - Research area:Raumfahrt
DLR - Program:R - no assignment
DLR - Research theme (Project):R - no assignment
Location: Jena
Institutes and Institutions:Institute of Data Science > Citizen Science
Deposited By: Contreras, Jhonatan
Deposited On:23 Jan 2020 15:52
Last Modified:23 Jan 2020 15:52

Repository Staff Only: item control page

Browse
Search
Help & Contact
Information
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.